LiDAR RoboSense Fairy

What Fairy adds to a perception stack

The RoboSense Fairy is designed for robotic 3D perception pipelines, with a focus on measurement accuracy and point cloud density. Key parameters for algorithmic use include 0.5 cm accuracy, a 360° × 32° FoV, and a range up to 150 m (with 80 m @ 10%).

Its angular resolution (0.25° (H) / 0.33° (V)) and throughput (up to ~1,370,000 pts/s in the 96-line version) help preserve useful geometry for obstacle detection, segmentation, and SLAM, especially for thin or low-contrast objects. The 10 Hz (adjustable) setting supports tuning the trade-off between latency, scene dynamics, and compute load.

For integration, UDP over Ethernet (100Base-TX / 100Base-T1) carries 3D coordinates, reflectivity, and a timestamp, supporting logging, test reproducibility, and use within a robotics middleware. Time synchronization (GPRMC + 1PPS, PTP, gPTP) is useful for multi-sensor setups (LiDAR + cameras + IMU) where time alignment matters. Embedded deployment is supported by < 10 W power consumption and 9–32 V input, with IP67 / IP6K9K protection and an operating range of -40°C to +60°C. The Class 1 laser (940 nm) suits shared test environments (labs, demos, industrial sites).

Applications and project examples

• 3D mapping and reconstruction: dense geometry capture to model scenes (outdoor surveys, structure reconstruction, terrain capture).
• Autonomous navigation and obstacle avoidance: using the 3D cloud to detect obstacles and secure trajectories (mobile robot in shared areas, indoor/outdoor test tracks).
• Localization and SLAM: integration in a LiDAR localization pipeline, using timestamps and synchronization for multi-sensor fusion.
• Multi-sensor fusion: LiDAR/camera/IMU time alignment via 1PPS and PTP/gPTP (perception rig, instrumented platform, test bench).
• Service robotics: integration on delivery robots and cleaning robots when 360° perception and point density are priorities.
• Logistics and industrial mobility: autonomous forklifts, navigation in mixed-traffic areas, detection of obstacles and edges.
• Drones and lightweight systems: integration on UAVs and portable mapping devices thanks to the compact format and low weight.

Available versions

• 96 lines: ~1,370,000 pts/s, to maximize point cloud density (detailed mapping, fine detection).
• 48 lines: ~685,000 pts/s, for a balance between throughput and processing.